Analysis, design and development of a data solution for a selected hotel

The main aim of the thesis is to prepare an analytical solution to support users in revenue management. The theoretical basis of the thesis is based on research of academic and book sources, which offers readers an up-to-date view of the state of knowledge in this field. To better understand the situation in the hotel market, data from the Czech and European Statistical Office were analyzed. Research on current trends in data analytics for the hotel and revenue management area was not forgotten. The author tried to transmit practical experience through a chapter on hotel analytics in order to better understand the environment and factors affecting the selected segment. The description of hotel analytics with a focus on revenue management can be enriching for hoteliers who are considering implementing dynamic pricing practices. The data solution consists of two parts - the first contains a set of reports with focus on revenue management to support users in pricing and demand analysis activities, while the second part is dedicated to advanced analytics. The theses describes the process of analysis, design and implementation of the data solution and provides a practical view into the capabilities of the Keboola platform for a small business. Advanced analytics is the second part of the data solution offering a demonstration of the potential of using a Python machine learning model to predict the likelihood of cancellation for hotel bookings, with the business objective of reducing cancellation rates. The data solution was built based on an analysis of the current state and the needs from the hotel. The proposed architecture allows the solution to be extended to other properties using the same hotel information system and respects the limited financial budget of the hotel. Moreover, it can also be an inspiration for readers to implement data solutions for small businesses.